How Insurers Are Boosting Growth and Efficiency With Domain-Based AI Strategies

Why Insurers Should Adopt a Domain-Based AI Strategy

Many insurers have begun integrating AI, but few see benefits across their entire business. McKinsey's recent report highlights that carriers focusing on how AI can improve specific areas—like claims, underwriting, or distribution—are achieving stronger results. This domain-based approach has boosted new agent sales conversion rates by 10% to 20% and increased premiums by roughly 10% to 15%.

Applying AI Across Insurance Functions

In life and health insurance, natural language processing (NLP) can enhance sales by creating personalized outreach and assisting with product research. Cognitive AI helps handle prospective clients’ questions efficiently. After a policy is sold, robotic process automation (RPA) reduces manual work in form-filling and customer enrollment. Throughout the policy lifecycle, machine learning helps cut costs and risks by predicting fraud and minimizing litigation.

AI Leaders Outperform the Market

McKinsey notes that over the last five years, insurers leading in AI adoption delivered shareholder returns 6.1 times higher than those lagging behind. This gap is much larger than in other industries, where the lead tends to be two or three times.

Key AI Disciplines for Insurance

• Traditional Analytical AI: Identifies data patterns for decision-making.
• Generative AI: Understands unstructured data better and enables hyper-personalized, empathetic responses.
• Agentics: Automates complex workflows at unprecedented levels.

These disciplines support AI use in sales productivity, underwriting accuracy, claims management, voice-assisted customer service, and back-office operations like finance, actuarial, and IT.

Leadership’s Role in AI Success

For AI to drive growth, executives must view it as more than a tool for efficiency. Leadership should set clear, measurable business goals linked to AI and develop a roadmap showing how AI can strengthen each business function, rather than deploying it in isolated pockets.

Modularity Speeds AI Adoption

One advantage of AI is its modularity: the same AI engine can power different applications. For example, generative AI can support IT help desks, marketing content creation, or legal document drafting, speeding up implementation and reducing costs.

Building the Right Team and Infrastructure

• About 80% of digital talent should be kept in-house to maintain control and expertise.
• A dedicated HR team can attract and retain tech-savvy employees comfortable with AI.
• The technology stack must be scalable and flexible to support multiple AI applications and adapt quickly to new tools.
• Embedding data throughout the organization ensures full use of institutional knowledge.

Insurers looking to deepen their AI skills can explore practical training options available at Complete AI Training, offering courses tailored for finance and insurance professionals.